library(tidyverse)
library(rtweet)

Search tweets

search_tweets

{r}
bts <- search_tweets("#BTS", n = 5000, include_rts = FALSE)

bts_dynamite <- search_tweets("#BTS dynamite", n = 5000, include_rts = FALSE)
bts
bts_dynamite

get friends

@john_little

get followers

timelines

min(created_at) max(created_at)
2015-04-21 13:59:55 2020-10-27 20:49:18
rg_tmls %>% 
  dplyr::filter(created_at > "2016-01-01") %>%  
  dplyr::group_by(screen_name) %>%
  ts_plot("weeks", trim = 1L) +
  ggplot2::geom_point() +
  geom_smooth(se = FALSE, color = "cadetblue") +
  colorblindr::scale_color_OkabeIto() +
  hrbrthemes::theme_ipsum(grid = "Y") +
  ggplot2::theme(
    legend.title = ggplot2::element_blank(),
    legend.position = "bottom", 
    plot.title = ggplot2::element_text(face = "bold")
    ) +
    ggplot2::labs(
    x = NULL, y = NULL,
    title = "Frequency of Twitter statuses",
    subtitle = "Twitter status (tweet) counts aggregated by week from Jan. 2016",
    caption = "Source: Data collected from Twitter's REST API via rtweet"
  )

NA
NA

get_favorites

search users

gullah <- search_users("#gullah", n = 1000)
Searching for users...
Finished collecting users!
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